Nowadays, sentiment analysis has become a hot research topic in the natural language processing field. The automated and semi-supervised way of text sentiment analysis makes a high value on practicing and theory studies. The sentiment orientation algorithm based on sentiment lexicon is an important approach in text sentiment analysis. Constructing a sentiment lexicon effectively is a basic task in the text sentiment analysis. However, Chinese words are very ambiguous in different domains. Meanwhile, different areas of sentiment words also have the characteristic of specialized. To solve these problems, we propose a semi-supervised sentiment orientation classification algorithm based on word vector similarity (SO-WV). Experiments show that, the algorithm can classify the sentiment orientation of words effectively. This algorithm has the versatility in different areas, and also offers professional and specialized characteristics.